Research On Vehicle Routing Optimization Of S Company Cold Chain Distribution Based On Traffic Information Updating

In recent years,the city cold chain distribution industry has developed rapidly,many enterprises use cold chain distribution to ensure the quality of food,but compared with normal temperature distribution,cold chain distribution has high energy consumption and high cost.Therefore,reasonable planning of distribution center location and distribution path has become an important way for enterprises to achieve energy saving,cost reduction,high efficiency and quality.However,the existing methods ignore the time-varying and complexity of the traffic network to a certain extent when solving the path optimization problem,and do not restore the distribution scene well,which makes the actual utility of the planned distribution path lack.This paper takes s company’s organic agricultural products distribution network as the research object,on the basis of determining the location of distribution center,considering the traffic information update,based on the idea of pre optimization and dynamic adjustment,provides a practical and feasible scheme for s company’s cold chain distribution path optimization.The specific research contents and related conclusions are as follows:First of all,this article briefly introduces the development status of the company’s organic agricultural product distribution network through field investigation of S company,analyzes and summarizes the main problems existing in the company’s distribution network,namely,the small scale of the distribution center,the unreasonable location selection,and the unscientific distribution route planning.In addition,in order to illustrate the necessity of S company to optimize the location and distribution route of the distribution center,this paper uses the GM(1,1)model in the gray forecast to predict the company’s offline sales of organic agricultural products in the next five years.The forecast results show that the offline sales volume of organic agricultural products of S company will show a rapid increase in the next five years.By 2025,the daily average distribution volume will reach 12.75 tons,with a year-onyear growth of 300%,with strong growth momentum.Therefore,if the existing problems of S company cannot be solved,it will be difficult to respond to the market demand of the rapid growth in the future in time,which will hinder the development of the company.Secondly,the paper uses AHP and fuzzy evaluation to select the distribution center,and takes the location result as the distribution center of path optimization.Considering the different traffic congestion in early peak period,the shortest path selection does not necessarily take the least time and the distribution cost is not necessarily the lowest.In the pre optimization stage,the paper constructs a multi distribution center based on initial traffic information and determines the pre optimal distribution path by taking the minimum total cost of vehicle use cost,transportation cost,refrigeration cost,cargo loss cost and penalty cost as the objective function;In the dynamic adjustment stage,a general path optimization model with the minimum total cost of distribution as the objective function is constructed,and each distribution path is adjusted dynamically according to the updated traffic information.In addition,the paper also gives the specific steps of genetic simulated annealing algorithm to solve the path optimization problem of S company.Finally,based on the questionnaire feedback and the actual distribution information of S company,this paper designs the distribution path optimization scheme based on the location of the distribution center of S company,and compares the optimization plan with the distribution plan before optimization.The results show that: compared with the current distribution scheme,the optimized distribution scheme uses less one refrigerator car,saves 328.55 yuan in daily distribution cost,and shortens the total distribution time by 0.9 hours,which verifies the effectiveness and feasibility of the model and method in this paper.On this basis,this paper puts forward the corresponding development suggestions for s company.